Random sampling is an appealing approach to build synopses of large data streams because random samples can be used for a broad spectrum of analytical tasks. Users are often inter...
We consider the problem of maintaining aggregates and statistics over data streams, with respect to the last N data elements seen so far. We refer to this model as the sliding wind...
Mayur Datar, Aristides Gionis, Piotr Indyk, Rajeev...
Integration over a domain, such as a Euclidean space or a Riemannian manifold, is a fundamental problem across scientific fields. Many times, the underlying domain is only acces...
The problem of skyline computation has attracted considerable research attention. In the categorical domain the problem becomes more complicated, primarily due to the partially-or...
Nikos Sarkas, Gautam Das, Nick Koudas, Anthony K. ...
We consider the problem of semantic load shedding for continuous queries containing window joins on multiple data streams and propose a robust approach that is effective with the ...